Entropy-based optimization strategies for convolutional neural networks
NN Gowdra - 2021 - openrepository.aut.ac.nz
Deep convolutional neural networks are state-of-the-art for image classification and
significant strides have been made to improve neural network model performance which can …
significant strides have been made to improve neural network model performance which can …
[PDF][PDF] 基于Sobel 算子滤波的图像增强算法
王云艳， 周志刚， 罗冷坤 - 计算机应用与软件, 2019 - shcas.net
摘要针对传统图像增强算法对噪声比较敏感, 图像失真和细节信息丢失等不足,
提出一种基于Sobel 算子滤波的图像增强算法. 通过理想高通滤波和Sobel 算子提取出边缘掩膜 …
提出一种基于Sobel 算子滤波的图像增强算法. 通过理想高通滤波和Sobel 算子提取出边缘掩膜 …
A new evaluation function for face image enhancement in unconstrained environments using metaheuristic algorithms
Image enhancement is an integral component of face recognition systems and other image
processing tasks such as in medical and satellite imaging. Among a number of existing …
processing tasks such as in medical and satellite imaging. Among a number of existing …
Novel fuzzy type-II driven modified Anisotropic Diffusion filter framework for restoration and enhancement of Rician noise corrupted MR images
K Verma, S Srivastava, RK Mishra - Multimedia Tools and Applications, 2024 - Springer
Brain disorders are impacting billions of individuals worldwide. Magnetic Resonance (MR)
Imaging is the most widely used imaging modality to examine brain abnormalities. However …
Imaging is the most widely used imaging modality to examine brain abnormalities. However …
Quantitative evaluation of prospective motion correction in healthy subjects at 7T MRI
Purpose Quantitative assessment of prospective motion correction (PMC) capability at 7T
MRI for compliant healthy subjects to improve high‐resolution images in the absence of …
MRI for compliant healthy subjects to improve high‐resolution images in the absence of …
Examining convolutional feature extraction using Maximum Entropy (ME) and Signal-to-Noise Ratio (SNR) for image classification
Convolutional Neural Networks (CNNs) specialize in feature extraction rather than function
mapping. In doing so they form complex internal hierarchical feature representations, the …
mapping. In doing so they form complex internal hierarchical feature representations, the …
Optimizing Voltage for Effective X-ray Computed Tomography Scan: A Study on Varied Soil Bulk Densities and Container Sizes
J Singh, A Shmatok, A Sanz-Saez, S Brown… - …, 2024 - journals.ashs.org
Numerous studies have highlighted the role of X-ray computed tomography (X-ray CT) in
understanding root architecture. Nevertheless, setting definitive scanning parameters for …
understanding root architecture. Nevertheless, setting definitive scanning parameters for …
Detection of lung cancer using image segmentation
In modern days, image processing methods are widely adopted in the medical field for
enhancing the earlier detection of certain abnormalities, such as the breast cancer, lung …
enhancing the earlier detection of certain abnormalities, such as the breast cancer, lung …
Examining and mitigating kernel saturation in convolutional neural networks using negative images
Neural saturation in Deep Neural Networks (DNNs) has been studied extensively, but
remains relatively unexplored in Convolutional Neural Networks (CNNs). Understanding …
remains relatively unexplored in Convolutional Neural Networks (CNNs). Understanding …
Satellite Imagery Superresolution Based on Optimal Frame Accumulation
SA Stankevich, MO Popov, SV Shklyar… - … Symposium of Space …, 2022 - Springer
As actual spatial resolution continues to be a primary bottleneck for satellite imagery
interpretation, the aim of resolution enhancement remains very urgent. The resolution …
interpretation, the aim of resolution enhancement remains very urgent. The resolution …